HVAC service performance

ABSTRACT

A monitoring system is configured to monitor a property. The system includes a sensor that is configured to generate sensor data that reflects an attribute of the property. The system further includes an HVAC system that is configured to generate and provide conditioned air to the property and that is configured to generate HVAC system data that reflects an attribute of the HVAC system. The system includes a monitor control unit that is configured to determine that the HVAC system is likely malfunctioning. The control unit is configured to receive the sensor data. The control unit is configured to determine that the HVAC system is likely operating correctly. The control unit is configured to determine a cause of the HVAC system transitioning from likely malfunctioning to likely operating correctly. The control unit is configured to update a model that is configured to identify causes of HVAC system malfunctions.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.16/752,249, filed Jan. 24, 2020, which claims the benefit of U.S.application Ser. No. 62/796,227, filed Jan. 24, 2019. The disclosure ofeach of the foregoing applications is incorporated herein by reference.

TECHNICAL FIELD

This specification relates generally to HVAC analytics technology.

BACKGROUND

Heating, Ventilation, and Air Conditioning (HVAC) systems are used toprovide thermal comfort and acceptable indoor air quality to residentialor commercial facilities. Typically, HVAC systems exchanges or replacesair in a space to remove unpleasant smells, remove excessive moisture,maintain air circulation, and prevent stagnation of the interior air.

SUMMARY

The subject matter of the present disclosure is related to thetechniques for addressing heating, ventilation, and air conditioning(HVAC) alerts detected by a security system that utilizes one or moremachine-learning models. The machine-learning model can detect andidentify one or more alerts in a monitored property and take action toresolve the various types of alerts. In particular, the machine-learningmodel can utilize data provided from the monitored property (e.g., suchas sensor data, product data, thermostat data, and data corresponding tothe HVAC system) to detect whether a condition exists with the HVACsystem. This will give homeowners peace of mind as their HVAC system isautomatically monitored for HVAC problems that can be detected,identified, and addressed without the user performing any work. Inresponse to the machine-learning model detecting an issue with the HVACsystem, the security system can generate a classification based on theoutput of the machine-learning model. The security system can providethe classification to an external residential security service, such asa central station, that monitors one or more residential properties in aparticular area. The central station can address the classificationreceived from the security system to resolve the HVAC issue of themonitored property.

The central station can reach out to the owner of the monitored propertyto alert the owner of the monitored property regarding the HVAC issue.In particular, a user at the central station can contact the owner todiscuss the HVAC issue. Once the owner at the monitored propertyconfirms of the HVAC issue, the central station can contact one or moreHVAC contractors to dispatch an HVAC technician to the monitoredproperty to address the HVAC issue. The central station can also log theclassification received by the security system to identify similarissues corresponding to other properties in its area.

In some implementations, the security system can detect when a servicehas been performed at the monitored property. In particular, thesecurity system can use its machine-learning model to detect monitoredproperties that have transitioned from an issue status to a healthyperformance status. For example, the security system can use itsmachine-learning model to analyze whether an HVAC system has had itsthermostat module fixed. The machine-learning model can receive outputfrom the monitored property that includes sensor data, product data,data from the HVAC system, and data from the owner of the monitoredproperty to produce an output that indicates whether the monitoredproperty has transitioned from the issue status to the healthyperformance status. Additionally, the security system can communicatewith the owner of the monitored property by requesting through theowner's client device. In response to receiving the owner's input (e.g.,whether an HVAC technician performed a service on an HVAC system), thesecurity system can provide the input from the owner as well the sensordata from the monitored property to refine and retrain themachine-learning model. In addition, the security system can verifythrough the owner that the scheduled service request for the monitoredproperty resulted in a repaired component in the monitored property(e.g., such as a repaired HVAC system.) The security system can assessthe productivity of the service performed by the HVAC technician on theHVAC system. The security system may record service times received froman owner or HVAC technician in order to assist with assessing the HVACsystem performance before and after the visit and determine howaffective the visit was. This information is valuable to the homeownerand the dealer, and can be used as a metric to rate the performance ofan HVAC technician.

According to an innovative aspect of the subject matter described inthis specification, a monitoring system is configured to monitor aproperty. The monitoring system includes a sensor that is configured togenerate sensor data that reflects an attribute of the property; an HVACsystem that is configured to generate and provide conditioned air to theproperty and that is configured to generate HVAC system data thatreflects an attribute of the HVAC system; and a monitor control unit.The monitor control unit is configured to receive, during a first timeperiod, one or more first samples of HVAC system data; based on the oneor more first samples of HVAC system data, determine that the HVACsystem is likely malfunctioning; receive, during a second time periodthat is after the first time period, the sensor data; receive, during athird time period that is after the second time period, one or moresecond samples of HVAC system data; based on the one or more secondsamples of HVAC system data, determine that the HVAC system is likelyoperating correctly; based on the sensor data, determine a cause of theHVAC system transitioning from likely malfunctioning to likely operatingcorrectly; and update a model that is configured to identify causes ofHVAC system malfunctions using data indicating the cause of the HVACsystem transitioning from likely malfunctioning to likely operatingcorrectly.

These and other implementations can each optionally include one or moreof the following features, alone or in combination. The monitor controlunit is configured to receive, during a fourth time period that is afterthe third time period, one or more third samples of HVAC system data;based on the one or more third samples of HVAC system data, determinethat the HVAC system is likely malfunctioning; provide the one or morethird samples of HVAC system data as an input to the model; and receive,from the model, data indicating a likely cause of the HVAC system ismalfunctioning. The monitor control unit is configured to determine thecause of the HVAC system transitioning from malfunctioning to operatingcorrectly by determining that an individual repaired the HVAC system;and update the model that is configured to identify causes of HVACsystem malfunctions using the data indicating the cause of the HVACsystem transitioning from malfunctioning to operating correctly byupdating the model using data indicating that the individual repairedthe HVAC system. The monitor control unit is configured to determinethat the individual repaired the HVAC system by analyzing the sensordata; and, based on the sensor data, determining that the attribute ofthe property did not match activity patterns of a resident of theproperty.

The monitor control unit is configured to determine that the individualrepaired the HVAC system by receiving, from a resident of the property,data confirming that an individual repaired the HVAC system. The monitorcontrol unit is configured to determine the cause of the HVAC systemtransitioning from malfunctioning to operating correctly by determiningthat no repair to the HVAC system was performed; and update the modelthat is configured to identify causes of HVAC system malfunctions usingthe data indicating the cause of the HVAC system transitioning frommalfunctioning to operating correctly by updating the model using dataindicating that no repair to the HVAC system was performed. The monitorcontrol unit is configured to determine that no repair to the HVACsystem was performed by analyzing the sensor data; and, based on thesensor data, determining that a window or door of the property was openfor at least a threshold period of time. The monitor control unit isconfigured to, based on determining that the HVAC system is likelymalfunctioning, provide, for output, a request for a repair to beperformed on the HVAC system. The monitor control unit is configured to,based on determining that the HVAC system is likely malfunctioning,initiate a communication with a resident of the property. The modelincludes one or more neural networks and is trained using machinelearning.

Other implementations of this aspect include corresponding systems,apparatus, and computer programs recorded on computer storage devices,each configured to perform the operations of the methods.

The details of one or more implementations of the subject matterdescribed in this specification are set forth in the accompanyingdrawings and the description below. Other features, aspects, andadvantages of the subject matter will become apparent from thedescription, the drawings, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a contextual diagram of an example system for monitoring HVACservices in a monitored property.

FIG. 1B is another contextual diagram of an example system formonitoring HVAC services in a monitored property.

FIG. 2 is a flowchart of an example process for notifying a centralstation of an HVAC condition at the monitored property based on obtainedsensor data from the monitored property.

FIG. 3 is a flowchart of an example process for using a trained model todetermine whether an HVAC service was completed and verifying theresults of the trained model.

FIG. 4 is a flowchart of an example process for determining whether anHVAC issue still exists after receiving an indication that an HVACtechnician is scheduled to fix the HVAC issue.

FIG. 5 is a block diagram of an example of a home monitoring system thatmay utilize various components to monitor an HVAC.

DETAILED DESCRIPTION

FIG. 1A is a contextual diagram of an example system 100 for monitoringHVAC service in a monitored property 102. Though system 100 is shown anddescribed including a particular set of components including a controlunit server 104, a network 106, speakers 108, camera 110, lights 112,sensors 114, home devices 116, air conditioner (or outdoor compressor)126, HVAC system 146, network 158, security system 160, central station162, HVAC database 164, and HVAC dealers 166 the present disclosure neednot be so limited. For instance, in some implementations the integratedsecurity environment for monitoring the HVAC system 146 of the monitoredproperty may use only a subset of the aforementioned components. As anexample, there may be implementations that do not use the speakers 108.Similarly, there may be implementations that the security system 160 isstored in the control unit server 104. The central station 162 can alsobe stored in the control unit server 104, instead of separate from thecontrol unit server 104. Yet, other alternative exemplary systems alsofall within the scope of the present disclosure such as a system thatdoes not use a control unit server 104. For these reasons, the system100 should not be viewed as limiting the present disclosure to anyparticular set of necessary components.

As shown in FIG. 1A, a monitored property 102 owned by owner 130 ismonitored by a control unit server 104 that includes components withinthe monitored property 102. The integrated security system 100 furtherincludes an alarm panel 122 with a message display 124, a thermostat120, and an HVAC system 146, which includes a return air duct 138, airduct 140, an air filter 142, a fan 144, a thermostat module 150, aheating module 148, an evaporator coil 152, air handling unit 154,refrigerant filled tubing 128, and supply air ducts 156A and 156B. Thethermostat 120 displays a temperature to set the temperature of themonitored property 102. The return air duct 138 includes a duct to carryair from a conditioned air space in the monitored property, such as inthe monitored property 102, to the air duct 140. The air filter 142includes a porous device that can be used to remove impurities or solidparticles from the air in the monitored property 102 that passes throughthe air duct 140. The fan 144 includes a mechanical device that createsa current of air, such as with the use of a fan, to move air through themonitored property 102.

The thermostat module 150 is a device within the HVAC system 146 used toreceive commands from the thermostat 120 and to convert the commandsinto instructions, instructing the HVAC system 146 to move thetemperature of monitored property 102 to a set temperature set by thethermostat 120. The heating module 148 produces heat to provide to themonitored property 102 through the HVAC system 146. The evaporator coil152 sits on top of the heating module 148 and can be used to cool airinside the monitored property 102. For example, the heating module 148can warm the air provided by the fan 144 and can pass the warm air toover the evaporator coil 152. The air that is provided from the fan 144and moved through the heating module 148 cools as it passes over theevaporator coil 152 because heat from the air transfers to therefrigerant in the refrigerant filled tubing 128. The refrigerant filledtubing 128 circulates refrigerant between the outdoor compressor 126 andthe evaporator coil 152. The outdoor compressor (e.g., air compressor)126 removes heat from the refrigerant, supplies air or other gas atincreased pressure to the HVAC system 146, and uses a fan to create acurrent of air. The air handling unit 154 includes a device to conditionand circulate air as part of the heating, ventilating, andair-conditioning process for the HVAC system 146. The supply air ducts156A and 1566 can provide resultant air from the HVAC system 146 toparticular rooms throughout the monitored property 102.

Additionally, the components within the monitored property 102 mayinclude one or more speakers 108, one or more cameras 110, one or morelights 112, one or more sensors 114, and one or more home devices 116.The one or more cameras 110 may include video cameras that are locatedat the exterior of the monitored property 102 near the front door 118,as well as located at the interior of the monitored property 102 nearthe front door 118. For example, a video camera may be placed in thebasement of the monitored property 102 for visually monitoring the HVACsystem 146 and send the images or video to the control unit server 104to send to a client device 132 owned by the owner 130. The one or moresensors 114 can include a motion sensor located at the exterior of themonitored property 102, a front door sensor that is a contact sensorpositioned at the front door 118, a pressure sensor that receives buttonpresses at a light device, an air flow sensor included in the air duct140 or the air handling unit 154, and a lock sensor that is positionedat the front door 118 and each window within the monitored property. Thecontact sensor may sense whether the front door 118 or the windows is inan open position or a closed position. The lock sensor may sense whetherthe front door 118 and each window is in an unlocked position or alocked position. The airflow sensor may sense whether air is flowingthrough the HVAC system 146 when turned-on to either heat or cool themonitored property 102. The one or more home devices 116 may includehome appliances such as a washing machine, a dryer, a dishwasher, anoven, a stove, a microwave, and a laptop, to name a few examples. Theone or more home devices 116 may also include a humidity sensor thatmonitors an amount of humidity in each room of the monitored property102. The control unit server 104 can adjust how much sun light is let into the monitored property 102 by adjusting a movement of shades coveringeach of the windows in the monitored property 102. Additionally, if themonitored property 102 is a commercial facility, the one or more homedevices 116 included in the commercial facility may include a printer, acopier, a vending machine, and a fax machine to name a few examples.

The control unit server 104 communicates over a wired or wirelessconnection over network 106 with connected devices such as each of theone or more speakers 108, one or more cameras 110, one or more lights112, one or more sensors 114, and one or more home devices 116 (washingmachine, a dryer, a dishwasher, an oven, a stove, a microwave, a laptop,etc.) to receive sensor data descriptive of events detected by the oneor more speakers 108, the one or more cameras 110, the one or morelights 112, the one or more sensors 114, and the one or more homedevices 116 in the monitored property 102. In some implementations, eachof the connected devices may connect via Wi-Fi, Bluetooth, or any otherprotocol used to communicate over network 106 to the control unit server104. The one or more speakers 108, the one or more cameras 110, the oneor more lights 112, the one or more sensors 114, and the one or morehome devices 116 can communicate with the security system 160 over thenetwork 158 and bypass the control unit server 104. Additionally, thecontrol unit server 104 can communicate over a long-range wired orwireless connection with a security system 160 over network 158. In someimplementations, the security system 160 is located remotely from themonitored property 102. In other implementations, the security system160 is located locally at the monitored property 102 within the controlunit server 104. The security system 160 communicates bi-directionallywith the control unit server 104. Specifically, the security system 160receives sensor data descriptive of events detected by the sensorsincluded in the monitoring system of the monitored property 102.Additionally, the security system 160 can transmit instructions to thecontrol unit server 104 for particular events. The control unit server104 and the security system 160 can also communicate directly with acentral station 162.

The central station 162 can monitor the monitored property 102, as wellas other (and, perhaps, many more properties), monitoring systemslocated at different monitored properties that are owned by varioususers. For example, the central station 162 can monitor many monitoredproperties by zip code, county, or city. In other implementations, thecentral station 162 can monitor monitored properties within aneighborhood. The central station 162 can also communicate with the HVACdealers 168 as well as the HVAC database 164.

The central station 162 can communicate with an HVAC database 164. TheHVAC database 164 can include one or more tables relatable to datacorresponding to HVAC systems of the central station 162's monitoredproperties. The one or more tables can include data describing issues ofHVAC systems, failure data of HVAC systems, data corresponding to HVACsystems that have changed from an issue state to a healthy state, anddata corresponding to HVAC systems that have changed from a health stateto an issue state. The tables can store sensor data from a correspondingmonitored property for each of these issues. The tables can also storeclassification label data corresponding to types of issues generated bythe security system 160. For example, these issues can correspond tobroken components, such as, broken thermostats, unresponsive burners,unresponsive air compressors, an unresponsive air compressor 126, lackof refrigerant in the refrigerant filled tubing 128, broken fan 144,broken evaporator coil 152, and low battery power, to name a fewexamples. The HVAC database 164 can also store indications when theseissues have been fixed. These indications can include determining that aHVAC technician has fixed the issue by sensor (and storing thecorresponding sensor data), notifications from owners that the HVACtechnician is scheduled to work on the issue, contact informationcorresponding to the owners of the monitored properties, record logs ofdata showing the central station 162 contacting the owner, andtranscriptions of the conversations between users at the central station162 and an homeowner of the monitored property. The HVAC database 164can also store raw sensor data corresponding to the monitored propertieswhen these issues occur. For example, the raw sensor data can includemotion detector data, proximity data, thermal data, and data from thehouse products, when one of these issues are detected by the controlunit server 104. The HVAC database 164 can receive this datacorresponding to HVAC issues from the control unit server 104 at themonitored property 102 and other monitored properties with an HVACsystem.

The HVAC database 164 can also receive thermostat data from a thermostatof a monitored property, such as thermostat 120 from monitored property102. For example, the thermostat information may comprise a currenttemperature, an operating state of the thermostat, information based onchanges of operating state of the thermostat such as when the thermostatis instructed to turn on and turn off, set points of the thermostatindicating target temperature, as well as outdoor temperature at thetime of a broken HVAC system, and whether auxiliary heat is included inthe monitored property 102. Additionally, the thermostat information mayinclude energy information associated with the HVAC system 146, a powerusage associated with the HVAC system 146, a humidity level of themonitored property 102, and various temperature readings from around themonitored property 102. Additionally, the control unit server 104 cantag the thermostat information from the thermostat 120 before providingthe thermostat information through the central station 162 to the HVACdatabase 164. For example, the tags can indicate whether the data fromthe thermostat corresponds to an HVAC system in an unhealthy state, ahealthy state, a maintenance operation state, and an off state. Thiswill allow the HVAC database 164 to store the raw sensor data and thethermostat data appropriately. The HVAC database 164 can also storeoutdoor temperature data corresponding to a particular monitoredproperty. Thus, when the control unit server 104 provides temperaturedata within the monitored property 102, the control unit server 104 canalso provide outdoor temperature and humidity information correspondingto the monitored property 102. The outdoor temperature data can beprovided to the HVAC database 164 and stored when the HVAC system is inan unhealthy state, a healthy state, a maintenance state, an off state,as the system transitions from an unhealthy state to the healthy state,and as the system transitions from the healthy state to the unhealthystate. The data stored in the HVAC database 164 can be fed into amachine-learning algorithm at the security system 160.

In some implementations, the security system 160 can store, train, andmanage a machine-learning algorithm. The machine-learning algorithm canalso be stored on the HVAC database 164. The machine-learning algorithmcan be used to perform a variety of tasks. For example, themachine-learning algorithm can be trained by the control unit server 104(or by the security system 160) to detect and identify issues associatedwith the HVAC system 146. For example, the security system 160 can use amachine-learning algorithm, such as a deep learning algorithm, ananomaly detecting algorithm, a linear regression algorithm, or a logicalregression algorithm, or a combination of various machine-learningalgorithms, to name a few examples.

The security system 160 can train the machine-learning algorithm toperform a variety of tasks. For example, the security system 160 cantrain its stored machine-learning algorithm to identify failurescorresponding to HVAC systems. The security system 160 can provideprevious failure data along with corresponding timestamps to amachine-learning algorithm. The failure data can include indicationsthat an HVAC system has failed, data showing broken components of afailed HVAC system, and raw sensor data that monitors the HVAC systemaround the time the HVAC system failed. The machine-learning algorithmcan use this training data to generate a trained model that identifiesand detects failed HVAC systems. Additionally, the security system 160can train the machine-learning algorithm using data that shows healthyHVAC systems. This helps the trained machine-learning algorithm todistinguish between healthy and non-healthy HVAC systems.

The security system 160 can also train the machine-learning algorithm todetect and identify HVAC systems that have transitioned from an issuestatus to a healthy status. This indication produced by themachine-learning algorithm can indicate when HVAC service was performedin a monitored property. For example, the security system 160 can usedata over a period of time that shows an HVAC system transitioningbetween an issue status and a healthy status. The data can includethermostat data over a period, such as 5 hours, outdoor temperature dataover the period of time, and raw sensor data monitoring the HVAC system146. The raw sensor data can be media data (e.g., video and photos) fromone or more cameras that monitor the HVAC system, audio data frommicrophones listening to the sounds produced by the HVAC system, thermalimaging data from thermal sensors that monitor the HVAC system, datafrom the alarm panel 122 that show issues with the HVAC system 146,motion data from motion sensors surrounding the HVAC system 146, andlock sensor data from doors containing the HVAC system 146. Other sensordata can be provided from the monitored property. Additionally, thesecurity system 160 can use data from house products to train themachine-learning algorithm. For example, the security system 160 can usedata from outdoor temperature sensors, outdoor barometers, temperaturesof various products in the monitored property 102, and data from aclient device of the owner of the monitored property 102. The securitysystem can also add the timestamp data to this transitioning trainingdata to predict likelihoods that the system has transitioned from anissue state to a healthy state to predict likelihoods of transitions atparticular times of the day. The training can be further based on HVACsystems at other monitored properties that have similar components. Thetraining can include how long it takes for an HVAC system to transitionto a health state after an issue has been detected.

The trained machine-learning algorithm can produce a likelihood that anHVAC system has transitioned between an issue status to a healthystatus. The likelihood can be statistical likelihoods, such aspercentages, that indicate how likely it is that the HVAC system hastransitioned to a healthy state from the issued state. This informationcan be used to verify with the homeowner that a service was performed onthe HVAC system and retrain the machine-learning algorithm if theservice was not actually performed. Additionally, the security system160 can retrain the machine-learning algorithm if the service wasperformed with additional HVAC system data and raw sensor data to finetune the machine-learning algorithm.

In some implementations, after the security system 160 has trained themachine-learning algorithm to a point that the machine-learningalgorithm can correctly identify issues and detect HVAC systems thattransitions between an issue state and a healthy state, the securitysystem 160 generates a trained model 170. The security system 160 cankeep a copy of the trained model 170 in its memory as well as provide acopy of the trained model 170 to the control unit server 104 at themonitored property 102. The trained model 170 can execute at the controlunit server 104 to quickly generate a notification of an issue ornotification of an HVAC system that has transitioned between an issuestate and a health state. The trained model 170 at the control unitserver 104 can monitor the data from the HVAC system 146, the speakers108, the microphones, the cameras 110, the lights 112, the sensors 114,the thermostat 120, and the home devices 116. In response to providingthe data from each of the devices in the monitored property 102 to thetrained model 170, the trained model 170 can produce an output based onits detection. For example, the output can indicate a predictedlikelihood of an issue existing or indicate a predicted likelihood of anHVAC system that has transitioned between an issue state to a healthystate. Alternatively, this step is performed on the security system 160.Based on the issue, the control unit server 104 can transmit anotification to the client device 132 of the owner 130. The trainedmodel 170 can also receive thermostat information corresponding tothermostat 120. The thermostat information can include currenttemperature of the thermostat, an operating state of the thermostat,information based on changes of operating state of the thermostat suchas when the thermostat is instructed to turn on and turn off, set pointsof the thermostat indicating target temperature, as well as a currentoutdoor temperature to search for and detect patterns of a failed HVACsystem 146.

The trained model 170 can not only predict if there is an issue with theHVAC system 146, but can also indicate if a particular component of theHVAC system 146 that may be at issue. For example, based on the datainput to the trained model 170, the trained model 170 can produce anindication that an issue exists with the component of the HVAC system146, such as the return air duct 138, air duct 140, the air filter 142,the fan 144, the thermostat module 150, the heating module 148, theevaporator coil 152, air handling unit 154, refrigerant filled tubing128, and supply air ducts 156A and 156B. The trained model 170 canproduce an error of the component type that appears to be broken bytraining the trained model 170 with raw sensor data and data from theHVAC system 146 that shows a particular component on the HVAC system 146is in fact broken or not working properly.

As illustrated in system 100, the trained model 170 can also execute onthe security system 160. The security system 160 can input data frommonitored property 102 and data from the HVAC database 164 to determine,based on analyzing trends with the input information, whether an issueassociated with the HVAC system 146 has occurred or whether the HVACsystem 146 has transitioned from an issue state to a healthy state. Theissue can include a predicted likelihood that the HVAC system 146 hasfailed and which particular component of the HVAC system 146 has failed.Alternatively, the trained model 170 can produce an indication that theparticular component, such as the fan 144, has now been fixed. Thistransition can indicate that an HVAC technician or another user hasfixed the HVAC system 146 or that a potential issue never existed. Thesecurity system 160 or the control unit server 104 can reach out to theuser, such as owner 130, to determine if an issue actually exists or ifa service was performed. If the user confirms of the issue or that theservice was performed, the security system 160 or the control unitserver 104 (or both) can retrain the trained model 170 in response toreceiving the user's answer along with raw sensor data and the type ofdetection.

The benefit of having the trained model 170 on both the control unitserver 104 and the security system 160 is to ensure that both models oneach system produce similar results when receiving information from themonitored property 102. Should the trained model 170 on the control unitserver 104 (or at the security system 160) detect a failure associatedwith the HVAC system 146 using the obtained thermostat information andother data from the monitored property 102 and the trained model 170located at the other location not detect a failure with similar inputdata, the security system 160 and the control unit server 104 cancommunicate with one another to resolve the difference. In someimplementations, each time the trained model 170 at one of the locationsoutputs an indication of a failure or success corresponding to the HVACsystem 146, the control unit server 104 and the security system 160communicate with one another to determine if the two systems result insimilar outputs. For example, the control unit server 104 provides inputto its trained model 170 to produce an error indicating a failureassociated with the HVAC system 146. In response, the control unitserver 104 can provide the detected HVAC failure and the input data tothe security system 160 via the network 158. If the security system 160determines its trained model 170 produces a different output with thesame input as the control unit server 104's trained model 170, then thesecurity system 160 can train its trained model 170 to detect thatparticular failure as detected by the trained model 170 at the controlunit server 104. This functionality also works in the reverse, where thesecurity system 160's trained model 170 detects an HVAC failure and thecontrol unit server 104's trained model 170 does not.

In some implementations, the trained model 170 may run at both thecontrol unit server 104 and at the security system 160 when the owner130 leaves the monitored property 102. In the example shown in FIG. 1A,an owner 130 may prepare to leave the monitored property 102. In doingso, the owner 130 may turn off each of the one or more lights 112, turnoff each of the one or more home devices 116, lock the front door 118,and close and lock each of the one or more windows. In someimplementations, the owner 130 may interact with a client device 132 toactivate a signature profile, such as “arm home” for the monitoredproperty 102. The client device 132 may display a web interface, anapplication, or a device specific for a smart home system. The clientdevice 132 can be, for example, a desktop computer, a laptop computer, atablet computer, a wearable computer, a cellular phone, a smart phone, amusic player, an e-book reader, a navigation system, a security panel,or any other appropriate computing device. In some implementations, theclient device 132 may communicate with the control unit server 104 usingthe network 106. The client device 132 may also communicate with thesecurity system 160 using the network 158 through the application of thesmart home system. The networks 106 and 158 may be wired or wireless ora combination of both and can include the Internet.

In some implementations, the owner 130 may communicate with the clientdevice 132 to activate a signature profile for the monitored property102. To illustrate, the owner 130 may first instruct the control unitserver 104 to set a signature profile for arming the monitored property102. For example, owner 130 may use a voice command to say “Smart Home,Arm Home.” The voice command may include a phrase, such as “Smart Home”to trigger the client device 132 to actively listen to a commandfollowing the phrase. Additionally, the phrase “Smart Home” may be apredefined user configured term to communicate with the client device132. The client device 132 can send the voice command to the controlunit server 104 over the network 106. The control unit server 104 maynotify the security system 160 that monitored property 102 is to bearmed. In addition, the control unit server 104 may set parameters toarm the monitored property 102 in response to receiving the voicecommand. Moreover, the control unit server 104 can send back aconfirmation to the client device 132 in response to arming themonitored property 102 and setting the armed parameters. For example,the control unit server 104 may send back a response to display amessage on the client device 132 that says “home armed.”

The importance of setting the signature profile indicates to the controlunit server 104 who to contact in case the trained model 170 detects anissue with one or more components of the HVAC system 146. For example,once the armed home signature profile is set, the control unit server104 immediately sends a notification to the client device 132 of theowner 130. The indication signifies to the client device 132 to displaya message to the owner 130 that the monitored property 102 is armed.Should the trained model 170 produce an error corresponding to the HVACsystem 146, the control unit server 104 provides that detected errornotification to the client device 132 of the owner 130. Additionally,the control unit server 104 provides the error to the security system160 to verify it produces the same error. Alternatively, the controlunit server 104 can provide the raw sensor data to the security system160 to determine if an error exists with the HVAC system 146.

In some implementations, upon the trained model 170's detection of afailure with the HVAC system 146 at either the control unit server 104or the security system 160, both the control unit server 104 and thesecurity system 160 log the detection of the failure of the HVAC system146 along with a timestamp in memory. Thus, a user, such as the owner130 or an HVAC technician 134, can review the logs at a later point intime to review the output of the trained model 170.

In some implementations, when the security system 160's trained model170 generates an output or a likelihood of an output, the securitysystem 160 proceeds to classify the output. The classification of theoutput can be a particular label that describes the output. The controlunit server 104 can also classify the output in a similar manner to thesecurity system 160. For example, the classification can be a code, atextual description, a category, a sub-category, or a number thatrepresents a type of the error of the HVAC system 146. Theclassification can describe the output that represents the issue withthe HVAC system 146. For example, the classification can describe aheating issue, a cooling issue, a filter issue, an issue with each ofthe one or more components, such as a blocking of the return air duct138, a blocking of the air duct 140, and an old air filter 142. Otherissues can include a broken fan 144, a broken thermostat module 150, abroken heating module 148, an old evaporator coil 152, an old airhandling unit 154, no refrigerant found in the refrigerant filled tubing128, and a blocking of the supply air ducts 156A and B. Other issues cancorrespond to the components of the HVAC system 146, the above mentionedonly as illustrated examples.

In some implementations, in response to the control unit server 104 orthe security system 160 generating a classification label correspondingto an output from a respective trained model 170, the classificationlabel can be provided to the central station 162. The central station162 can monitor many properties by a particular area and evencommunicate with HVAC dealers 166 to dispatch an HVAC technician to fixthe potential issue with the HVAC system 146. The central station 162can receive the classification of the issue from the security system 160corresponding to the monitored property 102 and take action to correctthe issue. For example, the central station 162 can process the receivedclassification of the issue to determine that fan 144 is broken. Inresponse to determining that the fan 144 corresponding to the HVACsystem 146 of the monitored property 102 is broken, the central station162 can immediately take action to reach out to the owner 130 of themonitored property 102 to verify that they are safe and to determine ifemergency HVAC services are needed. In particular, a user located at thecentral station 162 can call the client device 132 of the owner 130 tolet the owner 130 know that an issue was detected with the owner 130'sHVAC system 146. Alternatively, a computer can automatically call theclient device 132 and provide an automated voice recording to the owner130 indicating that an issue was detected with the owner 130's HVACsystem 146.

During the call, the central station 162 can ask the owner 130 if anHVAC technician should be dispatched to the monitored property 102 tocheck out the issue with the HVAC system 146. The owner 130 can respondto the central station 162's question by speaking or entering a key onthe keypad through his/her client device 132. If the owner 130 responds“No,” then the central station 162 can store the record of contactingthe owner 130 regarding the detected issue with the HVAC system 146 inmemory and disconnect the call. Alternatively, if the owner 130 responds“Yes,” then the central station 162 can indicate to the owner 130 thatan HVAC technician will be coming to the monitored property 102 soon anddisconnect the call. In response, the central station 162 cancommunicate with HVAC dealers 166 to dispatch an HVAC technician to theaddress of the monitored property 102. The central station 162 can senddirections to the address of the monitored property 102 to the HVACtechnician's client device. For example, as illustrated in system 100,the central station 162 can instruct the HVAC dealers 166 to dispatchHVAC technician 134 to the monitored property 102. The central station162 can transmit directions of the address of the monitored property 102to the client device 136 of the HVAC technician 134.

For example, during stage (A), the owner 130 sets the parameters for the“arming home” signature profile that includes setting the configurationfor the control unit server 104 to monitor the HVAC system 146. In someimplementations, the control unit server 104, the corresponding sensors,and the home devices monitor the HVAC system 146 regardless of thesignature profile set at the monitored property 102. In particular, thecontrol unit server 104 can retrieve data at a particular intervalthroughout the day from the HVAC system 146, the speakers 108, themicrophones, the cameras 110, the lights 112, the sensors 114, thethermostat 120, and the home devices 116. The control unit server 104can poll each of these devices in the monitored property 102 every hour,24 hours, or once a week, to name a few examples. The owner 130 can setthe period with which the control unit server 104 polls these devices.In response to receiving the data from each of these devices, thecontrol unit server 104 can transmit the data 168 from each of thesedevices to the security system 160. The data 168 can include raw sensordata, thermostat data, and identification data corresponding to themonitored property 102. The control unit server 104 transmits the data168 over the network 158 to the security system 160.

During stage (B), the security system 160 receives the data 168 from thecontrol unit server 104. The security system 160 provides the data 168to the trained model 170 to identify a failure corresponding to the HVACsystem 146. The failure data can include an indication that the HVACsystem 146 has failed, such as a likelihood that a particular componentof the HVAC system 146 has broken, or an indication that a particularcomponent of the HVAC system 146 is inefficient and needs to bereplaced. The failure data can be found at a hidden layer of the trainedmodel 170 or an output layer of the trained model 170, or a combinationof both. The data 168 can be provided sequentially or in parallel to thetrained model 170 to produce an indication of a failure output.

During stage (C), the trained model 170 can output an indication 172corresponding to the HVAC system 146 in response to receiving the data168 as input. The indication 172 can indicate failure data ornon-failure data corresponding to the HVAC system 146. In someimplementations, the indication 172 can correspond to a particularlikelihood that the HVAC system 146 has failed or a likelihood that aparticular component of the HVAC system 146 has failed. For example, thetrained model 170 can output an indication 172 of a percentage that thefan 144 has broken, such as 60%. The security system 160 can comparethis output percentage to a threshold, such as 50%. If the securitysystem 160 determines the output percentage is greater than a threshold,then the security system 160 can flag that the HVAC system 146 has anissue. Alternatively, the security system 160 discards the outputpercentage and the corresponding sensor data 168.

During stage (D), the security system 160 generates a classification 174of the output generated by the trained model 170. In particular, theclassification 174 of the output can include a particular label ordepiction that describes the output. Additionally, the control unitserver 104 can perform the classification of its trained model 170'soutput. For example, the classification 174 of the output can be a code,such as FRNACE or BLOWR, a textual description, such as “Broken Furnace”or “Old air filter.” Additionally, the classification 174 can be acategory, such as “Broken” or “Inefficient,” or a number that representsa type of error, such as “002” that represents a broken thermometer. Thesecurity system 160 can generate multiple classifications for aparticular output that includes a code, a textual description, and anumber, for example. Other example combinations are possible.

During stage (E), the security system 160 transmits the generatedclassification 174 that describes the output from the trained model 170to the central station 162. The security system 160 transmits thegenerated classification 174 to the central station 162 over the network158. Additionally, the security system 160 can transmit the generatedclassification 174, the indication 172, and the corresponding inputsensor data 168 to store in the HVAC database 164 for later retrieval.The security system 160 can later retrieve this data from the HVACdatabase 164 for re-training and fine-tuning the trained model 170located at the security system 160 and at the control unit server 104.

During stage (F), the central station 162 can receive the classificationlabel 174 corresponding to the indication 172 from the trained model170. In response, the central station 162 can take corrective action tofix the issue denoted by the classification label 174. For example, thecentral station 162 can determine from the classification label 174 thatthe supply air ducts 156A and 156B are blocked and not able to providewarm air to the monitored property 102. In response, the central station162 can contact the owner 130 of the monitored property 102 to verifythe owner 130 and corresponding members of the monitored property 102are safe. For example, a user at the central station 162 can call theclient device 132 of the owner 130 to verify that the owner 130 is safefrom harm. Alternatively, a voice recording can call the client device132 and provide a recorded message to the owner 130. The central station162 can also ask the owner 130 whether an issue exists with one or morecomponents of his/her HVAC system 146 or with the HVAC system 146itself. For example, the user at the central station 162 can speak tothe owner 130 and speak the phrase “Does an issue exist with your HVACfan?” The central station 162 can additionally ask to the owner 130whether an HVAC technician should be dispatched to the monitoredproperty 102 to fix the issue with the HVAC system 146.

During stage (G), the owner 130 can interact with his/her client device132 to provide a response 178 to the central station 162. For example,the owner 130 can speak to the client device 132 or interact with thekeys of the client device 132 to provide the response. The owner 130 mayopen an application on the client device 132, such as a smart homeapplication, to be able to communicate with the user or the voicerecording from the central station 162. In some implementations, theowner 130 can decline the notification 176 provided by the centralstation 162. In other implementations, the owner 130 can respond to thenotification 176 by indicating “Yes” 178 through the client device 132so the central station 162 can take further action to correct the issueproduced by the train model 170.

During stage (H), the central station 162 can receive the response 178from the owner 130 and proceed with communicating with the HVAC dealers166. In particular, the response 178 can indicate if the owner 130 issafe, whether the owner 130 notices an issue with his/her HVAC system146, and whether the owner 130 wishes an HVAC technician, such as HVACtechnician 134, be dispatched to the monitored property 102. If thecentral station 162 receives an indication that the owner 130 does notnotice an issue with his/her HVAC system 146, the central station 162can proceed to contact the HVAC dealers 166 to dispatch an HVACtechnician 134 to the monitored property 102. If the owner 130 does notwish to have an HVAC technician 134 dispatched to his/her monitoredproperty 102, the central station 162 can discard the response 178 fromthe owner 130 and store the raw sensor data, the indication 172, theclassification label 174 of the indication, and data identifying themonitored property 102 in the HVAC database 164 for later retrieval.This data can be used to retrain the trained model 170. If the owner 130does wish to have an HVAC technician 134 dispatched to check his/herHVAC system 146 at the corresponding monitored property 102, then thecentral station 162 can call the HVAC dealers 166 to dispatch an HVACtechnician 134 to the monitored property 102. The central station 162can provide detailed directions to the client device 136 of the owner134 as well data identifying the issue corresponding to the HVAC system146 that requires service. For example, the data identifying the issuecan include the indication 172, a classification 174 of the issue, andany descriptions of issues provided by the owner 130 when a user at thecentral station 162 spoke with the owner 130 asking if the owner 130recognized any issue with his/her HVAC system 146.

In one use case of how this works in a real-world environment, ahomeowner, such as Willow, is at her monitored property 102 on a hotSaturday in the summer when her air-conditioning stops working. Willowdoes not notice that her AC stops working since her monitored property102's temperature is still comfortable. The control unit server 104 andthe security system 160, in tandem or alone, detects an HVAC systemfailure and transmits the event to the central station 162 monitoringWillow's monitored property 102. The central station 162 determines thatthe failure is sever enough to contact Willow by initiating a 2-wayaudio call to discuss the issue with Willow's HVAC system. Willow is notconvinced that the AC is broken, but she notices that the temperatureinside is 76 F and her set point is 73 F. Willow verifies that no coldair is blowing out of the vents and she confirms with the centralstation that she would like to have a technician dispatched who canresolve the problem. The central station can relay this information backto the security system 160 or to the HVAC dealers 166, who matches herwith Jim's AC and Heating Corporation, a local HVAC dealer. Jim's AC andHeating Corporation is provided with Willow's address and contactinformation with Willow's approval, and an HVAC technician from Jim's ACand Heating Corporation is dispatched to her property 102 to fix theproblem before the monitored property 102 reaches an unsafe temperature.

By providing notifications and actions to/from the central station, thecentral station can automatically contact homeowners to make them feelsafe and comfortable. This streamlines the process of scheduling HVACappointments with homeowners and helps get customers immediateassistance in severe HVAC scenarios. HVAC dealers 166 can benefit of theuse of the central station by receiving more business, and thistechnology provides a new level of service that security dealers canoffer various customers at monitored properties. Overall, this newfeature provides tangible values to HVAC dealers and homeowners, inimproving the overall HVAC analytics system.

FIG. 1B is another contextual diagram of an example system 101 formonitoring HVAC services in a monitored property. System 101 includessimilar components and performs similar functions to system 100. Thesimilar components between system 100 and system 101 will not bedescribed again. In some implementations, the system 101 uses amachine-learning algorithm to detect and identify HVAC systemscorresponding to monitored properties, such as monitored property 102,that has transitioned from an issue status to a healthy status. Assystem 100 relates to detecting an issue with a HVAC system 146,verifying with the homeowner whether the individuals of the monitoredproperty 102 were safe, and whether to dispatch an HVAC technician tofix the potential issue with the HVAC system 146, system 101 relates toverifying a state change of the HVAC system 146 that indicates when theHVAC system 146 transitions from an issue state back to propertyperformance.

In some cases, this transition can indicate that an HVAC technicianserviced the HVAC system 146. However, not every state transition ofthis type will correspond to a servicing. For example, changes inweather patterns, routine maintenance performed by the end user, otherexternal factors may cause the machine-learning model to clear an issuealert corresponding to the HVAC system 146. In order to ensure that themachine-learning model produces correct results regarding the servicestate change of the HVAC system 146, the security system 160 can isolatethe issues resolved by confirming whether someone, such as an HVACtechnician, was in the monitored property 102 in the window of timewhether the HVAC system 146's behavior changed. If no one entered thehome during that window of time, the security system 160 can then inferthat no repair on the HVAC system 146 was completed. In addition, thecontrol unit server 104 and the security system 160 can work in tandemto determine, using video and imagery analytics, that activity in themonitored property 102 was not standard behavior, and in fact,indicative of a service call to an HVAC technician. The control unitserver 104 can also cross-reference motion sensor data and other sensordata in the monitored property 102 to confirm that certain parts of themonitored property 102, such as doors or areas within proximity to theHVAC system 146, were accessed in the expected service time window.

In some implementations, whether or not the sensor data is available atthe monitored property 102, one reliable way to verify whether the HVACsystem 146 was service includes prompting the owner of the monitoredproperty 102 to provide a confirmation of service with a notification.This notification provided by the owner, such as owner 130, would allowthe owner 130 to confirm or deny of such service to the HVAC system 146,and this feedback would be provided to the security system 160. Inparticular, the feedback from the owner 130, along with the raw sensordata and the previous output of the trained model 170 indicating a statechange in the service of the HVAC system 146 (albeit, a false detection)can be used to further train the existing trained model 170 or anothermachine-learning model that is specifically relied upon for detectingdata that indicates a state change (e.g., issue status changed tohealthy status). Additionally, this data can be stored in the HVACdatabase 164 that gives the security system 160 a good indication ofservice history, which can help the security system 160 and the centralstation 162 provide useful information to the user in the future. Forexample, as the security system 160 is monitoring a property 102, if thesecurity system 160 determines that an HVAC system 146 corresponding tothe monitored property 102 has gone several users with HVAC service froman HVAC technician or another user, it is beneficial for the securitysystem 160 to send reminders for maintenance or service, such asseasonal maintenance reminders or in app reminders with upsell offersfor maintenance plans. Additionally, the security system 160 can usethis information from the HVAC database 164 to avoid sending redundantmaintenance request reminders or advertising special offers in theapplication on the owner's client device 132.

For example, during stage (A′), similar to stage (A) from system 100,the control unit server 104, the corresponding sensors, and the homedevices monitor the HVAC system 146 at the monitored property 102. Inparticular, the control unit server 104 can retrieve data at aparticular interval from the HVAC system 146, the speakers 108, themicrophones, the cameras 110, the lights 112, the sensors 114, thethermostat 120, and the home devices 116. In response to receiving thisdata 168 at the control unit server 104, the control unit server 104 cantransmit the data 168 to the security system 160 over the network 158.The data 168 can include raw sensor data, thermostat data, andidentification data corresponding to the monitored property 102. Thecontrol unit server 104 may not have an idea what data 168 representsuntil the data 168 is provided to the trained model 170 located at thesecurity system 160. In some implementations, the trained model 170 canbe located at the control unit server 104, where data 168 is provided togenerate a representation of a potential state change of the HVAC system146.

During stage (B′), similar to stage (B) from system 100, the securitysystem 160 receives the data 168 from the control unit server 104. Thesecurity system 160 can store this data 168 in the HVAC database 164 forfuture retrieval. Additionally, the security system 160 can provide thedata 168 to the trained model 170 to identify whether a state changeoccurred from an unhealthy HVAC system 146 to a healthy HVAC system 146.The trained model 170 in system 101 can be similar or different from thetrained model 170 in system 100. The state change output from thetrained model 170 can indicate whether a service was performed on anHVAC system 146 by an HVAC technician or whether another user performeda service on the HVAC system 146. The state change data output by thetrained model 170 can be a likelihood, such as a percentage, that thischange occurred. The state change data can be found at a hidden layer ofthe trained model 170 or at an output layer of the trained model 170, ora combination of both. The data 168 can be provided to the trained model170 sequentially or in parallel to the nodes of the trained model 170 toproduce the indication.

During stage (C′), the trained model 170 can output an indication 172that indicates the HVAC system 146 has transitioned from an issue stateto a healthy state. The indication 172 cannot only indicate thistransition, but can also indicate what component of the HVAC system 146has been transitioned to properly work. For example, as in system 100,if the trained model 170 identifies that the fan 144 is broken, then insystem 101, the trained model 170 can output an indication that the fan144 has been fixed. The trained model 170 bases its output on the dataprovided by the sensors in the monitored property 102. For example, thisdata can show that user instructed the temperature of the monitoredproperty 102 to change from 67 degrees F. to 70 degrees F. and the HVACsystem 146 did warm the monitored property 102 to 70 F in a reasonabletime. Alternatively, the trained model 170 can output a likelihood, suchas a percentage, that the HVAC system 146 has transitioned to a healthstate from an issue state. For example, the trained model 170 can outputa likelihood of 65% that the HVAC system 146 has transition. Thesecurity system 160 can compare this output percentage to a thresholdpercentage, such as 50%. If the security system 160 determines that theoutput percentage is greater than the threshold, then the securitysystem 160 can flag that the HVAC system 146 has transitioned from theissue state to the healthy state. Alternatively, if the trained model170 outputs an indication that is less than the threshold percentage,the security system 160 can reach out to the owner 130 and possibly, theHVAC technician to verify if a service was performed. The securitysystem 160 can also verify with the owner 130 if the output percentageis greater than the threshold percentage, to ensure the trained model170 is performing as expected.

During stage (D′), the security system 160 can verify with the owner 130and the HVAC technician to determine if a service was properlyperformed. In particular, the security system 160 performs thisverification to check the quality of the service performed. Thus, if theoutput of the trained model 170 indicates that the service was performedbut the percentage was only 51%, the security system 160 can verify withboth users to determine if a service was performed. The security system160 can look up contact information corresponding to the user, such asan email address, a cellular telephone number, and a monitored property102 telephone number. Using this contact information, the securitysystem 160 can contact the owner 130.

During stage (E′), the security system 160 can transmit a notification176 to the client device 132 of the owner 130. For example, the securitysystem 160 can transmit a push notification to the client device 132that recites, “Was your HVAC fan fixed?” Alternatively, the securitysystem 160 can email the client device 132, can transmit a text to theclient device 132, or can call the client device 132 with an automatedvoice recording of “Was your HVAC fan fixed?” In other implementations,a user located at the security system 160 can call the owner 130 at theclient device 132 and speak with the owner 130 asking if the HVAC fanhas been fixed.

During stage (F′), the owner 130 can interact with his/her client device132 to provide a response 178 to the security system 160. For example,the owner 130 can also speak to the client device 132 or interact withkeys of the client device 132 to provide the response. The owner 130 mayopen an application on the client device 132, such as a smart homeapplication, to be able to communicate and respond to the securitysystem 160. In some implementations, the owner 130 can respond to themessage with a “No” transmitted by the security system 160.Alternatively, the owner 130 can respond to the message with a “Yes.”The response 178 can be provided back to the security system 160 overthe network 158.

During stage (G′), the security system 160 can receive the response 178and determine the intent of the response 178. For example, if theresponse 178 indicates that “Yes,” the HVAC fan was fixed, the securitysystem 160 can proceed with refining the trained model 170 with a properoutput that has been verified by the owner 130. Additionally, thesecurity system 160 can store the response 178, the corresponding data168 that includes the raw sensor data from the monitored property 102,and the indication 172 from the output of the trained model 170 in theHVAC database 164 for future retrieval at a later point in time. Thisdata can be used to retrain the trained model 170 or to train asubsequent new model. Alternatively, if the user indicates “No,” thenthe security system 160 infers from this that no HVAC service wasperformed on the HVAC system 146 and the trained model 170 produced anincorrect output. The security system 160 can take further steps toensure the trained model 170 reduces the number of subsequent erredoutputs. For example, the percentage threshold of the security system160 should be moved to 60% instead of 50%. In another example, thesecurity system 160 can retrain the trained model 170. For example, thesecurity system 160 can provide the sensor data 168, the user's response178, and the indication 172 from the output of the trained model 170 tothe input of trained model 170 for retraining purposes.

During stage (H′), the security system 160 can iteratively train thetrained model 170 with data until the trained model 170 produces thecorrect output. For example, the security system 160 can iterativelyprovide the sensor data 168, the user's response 178, and the indication172 of the output from the trained model 170 to the trained model 170,while changing the parameters of the trained model 170 each iteration,until the output of the trained model matches the user's response 178.In particular, if the indication 172 of the output from the trainedmodel 170 indicates that the HVAC system 146 had a state change fromissue status to healthy status, and the owner 130 verified that noservice was performed on the HVAC system 146, then the security system160 can iteratively update the parameters of the trained model 170 untilthe output is below the threshold with the same input. Once the trainedmodel 170 meets the desired expectation, the security system 160 cantransmit the newly retrained model 180 to its memory and transmit theretrained model 180 to the control unit server 104.

In some implementations, the security system 160 may obtain thermostatinformation from the monitored property 102 to determine whether theHVAC system 146 has been fixed. In particular, once the HVAC technician134 or another HVAC technician has performed a fix on the HVAC system146 as indicated by the detected failure event, the control unit server104 may obtain thermostat information from the thermostat 120 todetermine whether the HVAC system 146 has been fixed. For example, theHVAC model 170 may indicate no detected failure or inefficient componentin the HVAC system 146 after receiving thermostat information fromthermostat 120 over a particular period of time, such as a day, once theHVAC technician 134 fixes the HVAC system 146. By providing a nodetected failure or inefficient component over a particular period oftime, the HVAC model 170 becomes more robust to external factors such asend-user behavior or changing outdoor weather patterns that likely havelittle bearing on the HVAC system 146's performance, but could generatedeceiving model results for short periods of time. The HVAC technician134 may shut off the HVAC system 146 during maintenance and turn theHVAC system 146 back on after completion, at which the HVAC model 170may start to receive thermostat information. While the HVAC system 146is shut off, the HVAC model 170 may not receive any thermostatinformation.

The security system 160 can use thermostat information from themonitored property 102, data from the HVAC system 146, and additionalinformation to validate the productivity of a service call for an HVACtechnician. For example, the control unit server 104 may retainthermostat information from the thermostat 120, data from sensorsmonitoring the HVAC system 146 at the monitored property 102, andadditional information, such as recorded times of HVAC technician visitsto the monitored property 102. The control unit system 104 can then usethis information to assess the HVAC system 146 before the service andafter the service, to determine how effective the service was.Determining how effective the service was is valuable to the owner 130and the HVAC dealers 166, as this information can potentially be used asa metric to rate the performance of an HVAC technician 134. The securitysystem 160 can provide the thermostat information, the data from theHVAC system 146, and data indicating whether a service was performed onthe HVAC system 146 to the machine-learning model 170. Themachine-learning model 170 may produce an indication of whether failureexists with the HVAC system 146. The indication can be a percentage of alikelihood of a failure or a percentage of failed component at the HVACsystem 146. In one example, if the trained model 170 produces anindication of 0% failure after service performed, then the securitysystem 160 can note that the HVAC technician 134 was 100% effective infixing the issue with the HVAC system 146. In another example, if thetrained model 170 produces an indication of 50% failure after serviceperformed, then the security system 160 can note that the HVACtechnician 134 was 50% effective in fixing the issue with the HVACsystem 146. The security system 160 can provide its rating of HVACtechnicians to the HVAC dealers 166 for performance evaluation.

In some implementations, the security system 160 may test whether theHVAC system 146 is properly working when owner 130 is away from themonitored property 102. In particular, when the armed home signatureprofile is set, this indicates to the control unit server 104 that theowner 130 is away from the monitored property 102. Additionally, thesecurity system 160 may instruct the control unit server 104 to runspecific tests to test whether the HVAC system is properly working. Forexample, the control unit server 104 may be instructed to increase thetemperature of the monitored property to 85 degrees Fahrenheit and thendown to 45 degrees Fahrenheit. The control unit server 104 may determinean amount of time it took for the HVAC system 146 to raise and lower thetemperature of the HVAC system 146 to see if it falls within areasonable threshold. If the test falls outside a threshold, such as theperiod took an entire day, then the security system 160 may notify owner130 that the HVAC system 146 is not working properly. Additionally, thesecurity system 160 may perform tests, such as shutting the HVAC system146 off and on, measuring a difference between the desired temperatureset by the thermostat and the actual temperature in the monitoredproperty 102. If the difference between the desired the desiredtemperature set by the thermostat and the actual temperature in themonitored property 102 falls within a threshold, such as 1 degreeFahrenheit, then the HVAC system 146 is functioning as desired. In theevent that the HVAC system 146 is functioning as desired, the securitysystem 160 may notify owner 130 that the HVAC system 146 is functioningproperly. The security system 160 may communicate with the owner 130through the client device 132 or by sending a message through the alarmpanel 122 to display via message display 123 upon return of the owner130.

In one use case of how this works in a real-world environment, ahomeowner, such as Michael, has a smart thermostat in his monitoredproperty 102 that was installed on a 10-year-old furnace and airconditioning system. Michael does not get seasonal maintenance on hismonitored property 102 so his air conditioner stopped working thefollowing summer while he was on vacation. He received an alertnotification making him aware of the system issue, and he scheduled aservice call to resolve the issue. The day before Michael arrived home,a technician was able to repair the system. Shortly afterwards, thesecurity system 160 was able to detect that the furnace and airconditioning system was now working properly and notified Michael thatthe system was restored to normal working order. In that notification,the system requested confirmation of service. Michael confirmed that hisAC was repaired and was able to confirm that the refrigerant levels werelow, so the technician recharged the system. Now, the security system160 understands that the change in behavior was due to a service calland not changing weather patterns or user behavioral changes. Thesecurity system 160 also reset the timer on Michael's filter changereminder, as any service on an air conditioner would also come with achanged filter for the HVAC system 146. Now, Michael will not beinundated with a redundant filter change reminder right after a servicewas completed.

By detecting of HVAC service performed on an HVAC system, servicedealers can be held accountable for the quality of their HVAC service,assuring that homeowners are receiving the highest quality care, inaddition to providing an intelligent service to homeowners. In addition,this detection provides tangible values to dealers and customers, andbenefits the security system by allowing for a more targeted HVACtechnique for training new machine-learning models to detect specificissues due to a supply of ground truth data.

FIG. 2 is a flowchart of an example process 200 for determining an HVACsystem issue at the monitored property and alerting a customer of theHVAC system issue. Generally, the process 200 includes obtainingthermostat information and sensor data from a monitored property;determining an HVAC condition of an HVAC at the monitored property basedon an analysis of the obtained thermostat information and the sensordata from the monitored property using a trained model; generating datathat represents the HVAC condition based on predetermined conditions ofthe HVAC in the monitored property; and, providing the data thatrepresents the HVAC condition to a central station, where the centralstation can communicate with a customer of the monitored property toverify the HVAC condition with the customer and address the HVACcondition.

During 202, the security system 160 obtains thermostat information andsensor data from a monitored property 102. In some implementations, thecontrol unit server 104 can retrieve data at a particular intervalthroughout the day from the HVAC system 146, the speakers 108, themicrophones, the cameras 110, the lights 112, the sensors 114, thethermostat 120, and the home devices 116. The control unit server 104can poll each of these devices in the monitored property 102 every hour,24 hours, or once a week, to name a few examples. In response toreceiving the data from each of these devices, the control unit server104 can transmit the data 168 from each of these devices to the securitysystem 160. The data 168 can include raw sensor data, thermostat data,and identification data corresponding to the monitored property 102. Thecontrol unit server 104 transmits the data 168 over the network 158 tothe security system 160.

During 204, the security system 160 determines an HVAC condition of anHVAC at the monitored property based on an analysis of the obtainedthermostat information and the sensor data from the monitored propertyusing a trained model. The HVAC condition can indicate whether an issueexists or does not exist with the HVAC system. The security system 160receives the data 168 from the control unit server 104 and provides thedata 168 to the trained model 170 to identify the HVAC conditioncorresponding to the HVAC system 146. The HVAC condition can include anindication HVAC system 146 has failed, such as a likelihood that aparticular component of the HVAC system 146 has broken, or an indicationthat a particular component of the HVAC system 146 is inefficient andneeds to be replaced. The HVAC condition can be found at a hidden layerof the trained model 170 or an output layer of the trained model 170, ora combination of both. In some implementations, the indication 172 ofthe output from the trained model 170 can indicate failure ornon-failure corresponding to the HVAC system. For example, the trainedmodel 170 can output an indication 172 of a percentage that thethermostat module 150 is broken, such as 80%. The security system 160can compare this output percentage to a threshold. If the securitysystem 160 determines that the output percentage is greater than thethreshold, then the security system 160 can flag that the HVAC system146 has an issue. Alternatively, the security system 160 discards theoutput percentage and the corresponding sensor data 168.

During 206, the security system 160 generates data that represents theHVAC condition based on predetermined conditions of the HVAC in themonitored property. For example, the security system 160 generates aclassification label, such as classification 174, corresponding to theoutput generated by the trained model 170. The classification 174 caninclude a particular label or depiction that describes the output. Theclassification 174 can be based on previous classifications andcorresponding outputs stored in the HVAC database 164. For example, theclassification 174 of the output can be a code, such as FILTER or BLOWR,a textual description, such as “Broken Furnace” or “Old air filter.”Additionally, the classification 174 can be a category, such as “Broken”or “Inefficient,” or a number that represents a type of error, such as“002” that represents a broken thermometer. This data can be stored inthe HVAC database 164 for future usage by the security system 160 andthe control unit server 104.

During 208, the security system 160 provides the data that representsthe HVAC condition to a central station, whether the central station cancommunicate with a customer of the monitored property to verify the HVACcondition with the customer and address the HVAC condition. Inparticular, the security system 160 can transmit the generatedclassification 174 that describes the output of the trained model 170 tothe central station 162. The central station 162, upon receiving thegenerated classification 174 can take corrective action to address theHVAC condition. For example, the central station 162 can determine fromthe classification label 174 that the supply air ducts 156A and 156B areblocked and not able to provide warm air to the monitored property 102.In another example, the central station 162 can determine from theclassification label 174 that the fan 144 has died. The central station162 can then contact the owner 130 to verify and address the HVACcondition. The central station 162 transmit a notification to the owner130's client device 132 or a user can call the owner 130 to verifywhether the owner is safe and whether an issue exists with the HVACsystem 146. The owner 130 can respond to the response transmitted by thecentral station 162, by indicating whether an issue does or does notexist with the HVAC system 146.

In response, the central station 162 can receive the response from theowner 130 and proceed to communicate with the HVAC dealers 166. Inparticular, the response 178 can indicate if the owner 130 is safe,whether the owner 130 notices an issue with his/her HVAC system 146, andwhether the owner 130 wishes an HVAC technician, such as HVAC technician134, be dispatched to the monitored property 102. The central station162 can communicate with the HVAC dealers 166 to dispatch an HVACtechnician to the monitored property 102 if requested for by the owner130. If the owner 130 does not wish to have an HVAC techniciandispatched to his/her monitored property 102 because no issue existswith the HVAC system 146, the central station 162 can discard theresponse 178 from the owner 130 and store the raw sensor data, theindication 172, the classification label 174 of the indication, and dataidentifying the monitored property 102 in the HVAC database 164 forlater retrieval. Alternatively, if the owner 130 does not wish to havean HVAC technician dispatched to his/her monitored property 102 becausethe owner 130 plans to fix the issue with the HVAC system 146, thecentral station 162 can further store the central station 162 candiscard the response 178 from the owner 130 and store the raw sensordata, the indication 172, the classification label 174 of theindication, data identifying the monitored property 102, and anindication that the trained model 170 was correct in the HVAC database164.

FIG. 3 is a flowchart of an example process 300 for generating a modelfrom a machine-learning algorithm that can detect issues of an HVACsystem. Generally, the process 300 includes obtaining thermostatinformation and data from sensors of a monitored property; determiningHVAC service was completed based on analysis of the thermostatinformation and the data from sensors of the monitored property using atrained model; transmitting a request to a customer of the monitoredproperty to verify whether the HVAC service was completed; receiving aresponse to the request from the user indicating that the HVAC servicewas completed at the monitored property; providing the response, thethermostat information, and the data from sensors of the monitoredproperty to the trained model to update the trained model to detectsubsequent HVAC service completions.

During 302, the security system 160 obtains thermostat information andsensor data from a monitored property 102. 302 is similar to 202. Insome implementations, the control unit server 104 can retrieve data at aparticular interval throughout the day from the HVAC system 146, thespeakers 108, the microphones, the cameras 110, the lights 112, thesensors 114, the thermostat 120, and the home devices 116. The controlunit server 104 can poll each of these devices in the monitored property102 every hour, 24 hours, or once a week, to name a few examples. Inresponse to receiving the data from each of these devices, the controlunit server 104 can transmit the data 168 from each of these devices tothe security system 160. The data 168 can include raw sensor data,thermostat data, and identification data corresponding to the monitoredproperty 102. The control unit server 104 transmits the data 168 overthe network 158 to the security system 160.

During 304, the security system 160 determines HVAC service wascompleted based on analysis of the thermostat information and the datafrom sensors of the monitored property using a trained model. Inparticular, the security system 160 receives the data 168 from thecontrol unit server 104 and provides the data 16 to the trained model170 to identify whether a state change occurred of an unhealthy HVACsystem 146 to a healthy HVAC system 146. The state change output fromthe trained model 170 can indicate whether a service was performed on anHVAC system 146 by an HVAC technician or whether another user performeda service on the HVAC system 146. The state change data output by thetrained model 170 can be a likelihood, such as a percentage, that thischange occurred. The state change data can be found at a hidden layer ofthe trained model 170 or at an output layer of the trained model 170, ora combination of both. The data 168 can be provided to the trained model170 sequentially or in parallel to the nodes of the trained model 170 toproduce the indication.

The trained model 170 can produce an indication 172 that indicates theHVAC system 146 has transitioned from an issue state to a healthy state.The indication 172 cannot only indicate of this transition, but can alsoindicate what component of the HVAC system 146 has been transitioned toproperly work. The trained model 170 bases its output on the dataprovided by the sensors in the monitored property 102. For example, thisdata can show that user instructed the temperature of the monitoredproperty 102 to change from 67 degrees F. to 70 degrees F. and the HVACsystem 146 did warm the monitored property 102 to 70 F in a reasonabletime. Alternatively, the trained model 170 can output a likelihood, suchas a percentage, that the HVAC system 146 has transitioned to a healthstate from an issue state. The security system 160 can compare thisoutput percentage to a threshold percentage, such as 70%. The higher thepercentage, the more accurate the trained model 170 has to be indetecting a change in state with the HVAC system 146. If the securitysystem 160 determines that the output percentage is greater than thethreshold, then the security system 160 can flag that the HVAC system146 has transitioned from the issue state to the healthy state.Alternatively, if the trained model 170 outputs an indication that isless than the threshold percentage, the security system 160 can reachout to the owner 130 and possibly, the HVAC technician to verify if aservice was performed.

During 306, the security system 160 transmits a request to a customer ofthe monitored property to verify whether the HVAC service was completed.The security system 160 can look up contact information corresponding tothe user, such as an email address, a cellular telephone number, and amonitored property 102 telephone number. Using this contact information,the security system 160 can contact the owner 130. Thenotification/request transmitted to the owner 130 of the monitoredproperty 102 can be a push notification, an email, a text, an instantmessage, or a call to determine whether the HVAC service correspondingto the HVAC system 146 was completed.

During 308, the security system 160 receives a response 178 to therequest from the user indicating that the HVAC service was completed atthe monitored property 102. In particular, the owner 130 can interactwith his/her client device 132 to respond to the security system 160 toindicate either “No,” that that owner 130's corresponding HVAC system146 was not fixed, or “Yes,” that the owner 130's corresponding HVACsystem 146 was fixed. The response 178 can be provided back to thesecurity system 160 over the network 158 indicating that the HVACservice was completed.

During 310, the security system 160 provides the response, thethermostat information, and the data from sensors of the monitoredproperty to the trained model to update the trained model to detectsubsequent HVAC service completions. For example, the security system160 can retrain the trained model 170 using the sensor data 168, theuser's response 178, and the indication 172 of the output of the trainedmodel 170. Once the trained model 170 produces an output that is in linewith the user's response 178, the security system 160 can stop trainingthe model 170.

FIG. 4 is a flowchart of an example process 400 for performing one ormore thermostat tests to determine whether the HVAC system 146 isworking properly when the household is empty. Generally, the process 400includes receiving an indication from a customer that an HVAC technicianis scheduled to perform service on an HVAC at a monitored property tofix an issue with the HVAC; obtaining thermostat information and datafrom sensors of the monitored property after a scheduled service time ofthe HVAC has elapsed; determining the HVAC issue still exists based onan analysis of the thermostat information and the data from sensors ofthe monitored property using a trained model; and providing anotification to the customer of the monitored property indicating thatthe HVAC technician did not fix the issue with the HVAC.

During 402, the security system 160 receives an indication from acustomer that an HVAC technician is scheduled to perform service on anHVAC at a monitored property to fix an issue with the HVAC. In someimplementations, the owner 130 may indicate through his/her clientdevice 132 that an HVAC technician is scheduled to perform service, suchas fix the fan 144, on the HVAC system 146. The owner 130 can store thisindication in his calendar on the client device 132, which can bemonitored by the smart home application. Alternatively, the owner 130can indicate that an HVAC technician is coming to the monitored property102 at a particular time in response to the security system 160identifying an issue with the HVAC system 146. The owner 130 can alsocall, text, or email the central station 162 or the security system 160indicating a time and for what reason the HVAC technician is coming tofix the HVAC system 146.

During 404, the security system 160 obtains thermostat information anddata from sensors of the monitored property after a scheduled servicetime of the HVAC has elapsed. After a particular time period has elapsedsurrounding the time in which the HVAC technician was scheduled to fixthe HVAC system 146, the control unit server 104 can obtain thermostatand sensor data that monitors the HVAC system 146 to determine whetherthe HVAC system 146 was in fact fixed. In particular, the control unitserver 104 can retrieve data at a scheduled time following the HVACtechnician's appointment time. This can be 10 hours or a full day afterthe HVAC technician's appointment time. After that time has elapsed, thecontrol unit server 104 can retrieve data from the HVAC system 146, thespeakers 108, the microphones, the cameras 110, the lights 112, thesensors 114, the thermostat 120, and the home devices 116. In responseto receiving the data from each of these devices, the control unitserver 104 can transmit the data 168 from each of these devices to thesecurity system 160. The data 168 can include raw sensor data,thermostat data, and identification data corresponding to the monitoredproperty 102. The control unit server 104 transmits the data 168 overthe network 158 to the security system 160.

During 406, the security system 160 determines the HVAC issue stillexists based on an analysis of the thermostat information and the datafrom sensors of the monitored property using a trained model. Thesecurity system 160 receives the data 168 from the control unit server104 and provides the data 168 to the trained model 170 to determinewhether the HVAC condition corresponding to the HVAC system 146 stillexists. The output of the trained model 170 can be a percentage that iscompared to a threshold. If the security system 160 determines that theoutput percentage is greater than the threshold, then the securitysystem 160 can flag that the issue associated with HVAC system 146 stillexists. Alternatively, the security system 160 can flag that the issueassociated with HVAC system 146 no longer exists.

During 408, the security system 160 provides a notification to thecustomer of the monitored property indicating that the HVAC techniciandid not fix the issue with the HVAC. The security system 160 cantransmit a notification to the owner 130 of the monitored property 102indicating whether the issue associated with the HVAC system 146 stillexists or no longer exists. The notification can be a push notification,an email, a text, or can call the client device 132 of the owner 130indicating of the status of the issue corresponding to the HVAC system146.

FIG. 5 is a block diagram of an example of a home monitoring system 500that may utilize various components to monitor an HVAC system 146. Thehome monitoring system 500 includes a network 505, a control unit server510, one or more user devices 540 and 550, a monitoring applicationserver 560, and a central alarm station server 570. In some examples,the network 505 facilitates communications between the control unitserver 510, the one or more user devices 540 and 550, the monitoringapplication server 560, and the central alarm station server 570.

The network 505 is configured to enable exchange of electroniccommunications between devices connected to the network 505. Forexample, the network 505 may be configured to enable exchange ofelectronic communications between the control unit server 510, the oneor more user devices 540 and 550, the monitoring application server 560,and the central alarm station server 570. The network 505 may include,for example, one or more of the Internet, Wide Area Networks (WANs),Local Area Networks (LANs), analog or digital wired and wirelesstelephone networks (e.g., a public switched telephone network (PSTN),Integrated Services Digital Network (ISDN), a cellular network, andDigital Subscriber Line (DSL)), radio, television, cable, satellite, orany other delivery or tunneling mechanism for carrying data. Network 505may include multiple networks or subnetworks, each of which may include,for example, a wired or wireless data pathway. The network 505 mayinclude a circuit-switched network, a packet-switched data network, orany other network able to carry electronic communications (e.g., data orvoice communications). For example, the network 505 may include networksbased on the Internet protocol (IP), asynchronous transfer mode (ATM),the PSTN, packet-switched networks based on IP, X.25, or Frame Relay, orother comparable technologies and may support voice using, for example,VoIP, or other comparable protocols used for voice communications. Thenetwork 505 may include one or more networks that include wireless datachannels and wireless voice channels. The network 505 may be a wirelessnetwork, a broadband network, or a combination of networks including awireless network and a broadband network.

The control unit server 510 includes a controller 512 and a networkmodule 514. The controller 512 is configured to control an HVAC systemthat includes the control unit server 510. In some examples, thecontroller 512 may include a processor or other control circuitryconfigured to execute instructions of a program that controls operationof an HVAC system. In these examples, the controller 512 may beconfigured to receive input from sensors, thermostats, or other devicesincluded in the HVAC system and control operations of devices includedin the household (e.g., a shower head, a faucet, a dishwasher, etc.).For example, the controller 512 may be configured to control operationof the network module 514 included in the control unit server 510.

The network module 514 is a communication device configured to exchangecommunications over the network 505. The network module 514 may be awireless communication module configured to exchange wirelesscommunications over the network 505. For example, the network module 514may be a wireless communication device configured to exchangecommunications over a wireless data channel and a wireless voicechannel. In this example, the network module 514 may transmit alarm dataover a wireless data channel and establish a two-way voice communicationsession over a wireless voice channel. The wireless communication devicemay include one or more of a LTE module, a GSM module, a radio modem,cellular transmission module, or any type of module configured toexchange communications in one of the following formats: LTE, GSM orGPRS, CDMA, EDGE or EGPRS, EV-DO or EVDO, UMTS, or IP.

The network module 514 also may be a wired communication moduleconfigured to exchange communications over the network 505 using a wiredconnection. For instance, the network module 514 may be a modem, anetwork interface card, or another type of network interface device. Thenetwork module 514 may be an Ethernet network card configured to enablethe control unit server 510 to communicate over a local area networkand/or the Internet. The network module 514 also may be a voicebandmodem configured to enable the alarm panel to communicate over thetelephone lines of Plain Old Telephone Systems (POTS).

The HVAC system that includes the control unit server 510 includes oneor more sensors. For example, the monitoring system may include multiplesensors 520. The sensors 520 may include a temperature sensor, ahumidity sensor, a leaking sensor, or any other type of sensor includedin an HVAC system 146. The sensors 520 also may include an environmentalsensor, such as a temperature sensor, a water sensor, a rain sensor, awind sensor, a light sensor, a smoke detector, a carbon monoxidedetector, an air quality sensor, etc. The sensors 520 further mayinclude a health monitoring sensor, such as a prescription bottle sensorthat monitors taking of prescriptions, a blood pressure sensor, a bloodsugar sensor, a bed mat configured to sense presence of liquid (e.g.,bodily fluids) on the bed mat, etc. In some examples, the sensors 520may include a radio-frequency identification (RFID) sensor thatidentifies a particular article that includes a pre-assigned RFID tag.

The control unit server 510 communicates with the automation module 522and the camera 530 to perform monitoring. The automation module 522 isconnected to one or more devices that enable home automation control.For instance, the automation module 522 may be connected to one or morelighting systems and may be configured to control operation of the oneor more lighting systems. Also, the automation module 522 may beconnected to one or more electronic locks at the property and may beconfigured to control operation of the one or more electronic locks(e.g., control Z-Wave locks using wireless communications in the Z-Waveprotocol. Further, the automation module 522 may be connected to one ormore appliances at the property and may be configured to controloperation of the one or more appliances. The automation module 522 mayinclude multiple modules that are each specific to the type of devicebeing controlled in an automated manner. The automation module 522 maycontrol the one or more devices based on commands received from thecontrol unit server 510. For instance, the automation module 522 maycause a lighting system to illuminate an area to provide a better imageof the area when captured by a camera 530.

The camera 530 may be a video/photographic camera or other type ofoptical sensing device configured to capture images. For instance, thecamera 530 may be configured to capture images of an area within abuilding or within a HVAC system monitored by the control unit server510. The camera 530 may be configured to capture single, static imagesof the area and also video images of the area in which multiple imagesof the area are captured at a relatively high frequency (e.g., thirtyimages per second). The camera 530 may be controlled based on commandsreceived from the control unit server 510.

The camera 530 may be triggered by several different types oftechniques. For instance, a Passive Infra-Red (PIR) motion sensor may bebuilt into the camera 530 and used to trigger the camera 530 to captureone or more images when motion is detected. The camera 530 also mayinclude a microwave motion sensor built into the camera and used totrigger the camera 530 to capture one or more images when motion isdetected. The camera 530 may have a “normally open” or “normally closed”digital input that can trigger capture of one or more images whenexternal sensors (e.g., the sensors 520, PIR, door/window, etc.) detectmotion or other events. In some implementations, the camera 530 receivesa command to capture an image when external devices detect motion oranother potential alarm event. The camera 530 may receive the commandfrom the controller 512 or directly from one of the sensors 520.

In some examples, the camera 530 triggers integrated or externalilluminators (e.g., Infra-Red, Z-wave controlled “white” lights, lightscontrolled by the module 522, etc.) to improve image quality when thescene is dark. An integrated or separate light sensor may be used todetermine if illumination is desired and may result in increased imagequality.

The camera 530 may be programmed with any combination of time/dayschedules, system “arming state”, or other variables to determinewhether images should be captured or not when triggers occur. The camera530 may enter a low-power mode when not capturing images. In this case,the camera 530 may wake periodically to check for inbound messages fromthe controller 512. The camera 530 may be powered by internal,replaceable batteries if located remotely from the control unit server510. The camera 530 may employ a small solar cell to recharge thebattery when light is available. Alternatively, the camera 530 may bepowered by the controller 512's power supply if the camera 530 isco-located with the controller 512.

In some implementations, the camera 530 communicates directly with themonitoring application server 560 over the Internet. In theseimplementations, image data captured by the camera 530 does not passthrough the control unit server 510 and the camera 530 receives commandsrelated to operation from the monitoring application server 560.

The system 500 also includes thermostat 534 to perform dynamicenvironmental control at the property. The thermostat 534 is configuredto monitor temperature and/or energy consumption of an HVAC systemassociated with the thermostat 534, and is further configured to providecontrol of environmental (e.g., temperature) settings. In someimplementations, the thermostat 534 can additionally or alternativelyreceive data relating to activity at a property and/or environmentaldata at a property, e.g., at various locations indoors and outdoors atthe property. The thermostat 534 can directly measure energy consumptionof the HVAC system associated with the thermostat, or can estimateenergy consumption of the HVAC system associated with the thermostat534, for example, based on detected usage of one or more components ofthe HVAC system associated with the thermostat 534. The thermostat 534can communicate temperature and/or energy monitoring information to orfrom the control unit server 510 and can control the environmental(e.g., temperature) settings based on commands received from the controlunit server 510.

In some implementations, the thermostat 534 is a dynamicallyprogrammable thermostat and can be integrated with the control unitserver 510. For example, the dynamically programmable thermostat 534 caninclude the control unit server 510, e.g., as an internal component tothe dynamically programmable thermostat 534. In addition, the controlunit server 510 can be a gateway device that communicates with thedynamically programmable thermostat 534.

A module 537 is connected to one or more components of an HVAC systemassociated with a property, and is configured to control operation ofthe one or more components of the HVAC system. In some implementations,the module 537 is also configured to monitor energy consumption of theHVAC system components, for example, by directly measuring the energyconsumption of the HVAC system components or by estimating the energyusage of the one or more HVAC system components based on detecting usageof components of the HVAC system. The module 537 can communicate energymonitoring information and the state of the HVAC system components tothe thermostat 534 and can control the one or more components of theHVAC system based on commands received from the thermostat 534.

The system 500 further includes one or more integrated security devices580. The one or more integrated security devices may include any type ofdevice used to provide alerts based on received sensor data. Forinstance, the one or more control units 510 may provide one or morealerts to the one or more integrated security input/output devices.Additionally, the one or more control units 510 may receive one or moresensor data from the sensors 520 and determine whether to provide analert to the one or more integrated security input/output devices 580.

The sensors 520, the module 522, the camera 530, the thermostat 534, andthe integrated security devices 580 communicate with the controller 512over communication links 524, 526, 528, 532, and 584. The communicationlinks 524, 526, 528, 532, and 584 may be a wired or wireless datapathway configured to transmit signals from the sensors 520, the module522, the camera 530, the thermostat 534, and the integrated securitydevices 580 to the controller 512. The sensors 520, the module 522, thecamera 530, the thermostat 534, and the integrated security devices 580may continuously transmit sensed values to the controller 512,periodically transmit sensed values to the controller 512, or transmitsensed values to the controller 512 in response to a change in a sensedvalue.

The communication links 524, 526, 528, 532, and 584 may include a localnetwork. The sensors 520, the module 522, the camera 530, the thermostat534, and the integrated security devices 580 and the controller 512 mayexchange data and commands over the local network. The local network mayinclude 802.11 “Wi-Fi” wireless Ethernet (e.g., using low-power Wi-Fichipsets), Z-Wave, Zigbee, Bluetooth, “Homeplug” or other “Powerline”networks that operate over AC wiring, and a Category 5 (CAT5) orCategory 5 (CAT6) wired Ethernet network. The local network may be amesh network constructed based on the devices connected to the meshnetwork.

The monitoring application server 560 is an electronic device configuredto provide monitoring services by exchanging electronic communicationswith the control unit server 510, the one or more user devices 540 and550, and the central alarm station server 570 over the network 505. Forexample, the monitoring application server 560 may be configured tomonitor events (e.g., alarm events) generated by the control unit server510. In this example, the monitoring application server 560 may exchangeelectronic communications with the network module 514 included in thecontrol unit server 510 to receive information regarding events (e.g.,HVAC control events) detected by the control unit server 510. Themonitoring application server 560 also may receive information regardingevents (e.g., HVAC events) from the one or more user devices 540 and550.

In some examples, the monitoring application server 560 may route HVACdata received from the network module 514 or the one or more userdevices 540 and 550 to the central alarm station server 570. Forexample, the monitoring application server 560 may transmit the HVACdata to the central alarm station server 570 over the network 505.

The monitoring application server 560 may store sensor and image datareceived from the monitoring system and perform analysis of sensor andimage data received from the monitoring system. Based on the analysis,the monitoring application server 560 may communicate with and controlaspects of the control unit server 510 or the one or more user devices540 and 550.

The central alarm station server 570 is an electronic device configuredto provide alarm monitoring service by exchanging communications withthe control unit server 510, the one or more mobile devices 540 and 550,and the monitoring application server 560 over the network 505. Forexample, the central alarm station server 570 may be configured tomonitor HVAC events generated by the control unit server 510. In thisexample, the central alarm station server 570 may exchangecommunications with the network module 514 included in the control unitserver 510 to receive information regarding HVAC events detected by thecontrol unit server 510. The central alarm station server 570 also mayreceive information regarding HVAC events from the one or more mobiledevices 540 and 550 and/or the monitoring application server 560.

The central alarm station server 570 is connected to multiple terminals572 and 574. The terminals 572 and 574 may be used by operators toprocess HVAC events. For example, the central alarm station server 570may route HVAC data to the terminals 572 and 574 to enable an operatorto process the HVAC data. The terminals 572 and 574 may includegeneral-purpose computers (e.g., desktop personal computers,workstations, or laptop computers) that are configured to receive HVACdata from a server in the central alarm station server 570 and render adisplay of information based on the HVAC data. For instance, thecontroller 512 may control the network module 514 to transmit, to thecentral alarm station server 570, HVAC data indicating that a sensor 520detected a flow rate of air in the air handling unit 154. The centralalarm station server 570 may receive the HVAC data and route the HVACdata to the terminal 572 for processing by an operator associated withthe terminal 572. The terminal 572 may render a display to the operatorthat includes information associated with the HVAC event (e.g., the flowrate, the air duct the flow rate came from, the temperature of the airin the air duct, etc.) and the operator may handle the HVAC event basedon the displayed information.

In some implementations, the terminals 572 and 574 may be mobile devicesor devices designed for a specific function. Although FIG. 5 illustratestwo terminals for brevity, actual implementations may include more (and,perhaps, many more) terminals.

The one or more user devices 540 and 550 are devices that host anddisplay user interfaces. For instance, the user device 540 is a mobiledevice that hosts one or more native applications (e.g., the smart homeapplication 542). The user device 540 may be a cellular phone or anon-cellular locally networked device with a display. The user device540 may include a cell phone, a smart phone, a tablet PC, a personaldigital assistant (“PDA”), or any other portable device configured tocommunicate over a network and display information. For example,implementations may also include Blackberry-type devices (e.g., asprovided by Research in Motion), electronic organizers, iPhone-typedevices (e.g., as provided by Apple), iPod devices (e.g., as provided byApple) or other portable music players, other communication devices, andhandheld or portable electronic devices for gaming, communications,and/or data organization. The user device 540 may perform functionsunrelated to the monitoring system, such as placing personal telephonecalls, playing music, playing video, displaying pictures, browsing theInternet, maintaining an electronic calendar, etc.

The user device 540 includes a smart home application 542. The smarthome application 542 refers to a software/firmware program running onthe corresponding mobile device that enables the user interface andfeatures described throughout. The user device 540 may load or installthe smart home application 542 based on data received over a network ordata received from local media. The smart home application 542 runs onmobile devices platforms, such as iPhone, iPod touch, Blackberry, GoogleAndroid, Windows Mobile, etc. The smart home application 542 enables theuser device 540 to receive and process image and sensor data from themonitoring system.

The user device 550 may be a general-purpose computer (e.g., a desktoppersonal computer, a workstation, or a laptop computer) that isconfigured to communicate with the monitoring application server 560and/or the control unit server 510 over the network 505. The user device550 may be configured to display a smart home user interface 552 that isgenerated by the user device 550 or generated by the monitoringapplication server 560. For example, the user device 550 may beconfigured to display a user interface (e.g., a web page) provided bythe monitoring application server 560 that enables a user to perceiveimages captured by the camera 530 and/or reports related to themonitoring system. Although FIG. 5 illustrates two user devices forbrevity, actual implementations may include more (and, perhaps, manymore) or fewer user devices.

In some implementations, the one or more user devices 540 and 550communicate with and receive monitoring system data from the controlunit server 510 using the communication link 538. For instance, the oneor more user devices 540 and 550 may communicate with the control unitserver 510 using various local wireless protocols such as Wi-Fi,Bluetooth, Zwave, Zigbee, HomePlug (ethernet over powerline), or wiredprotocols such as Ethernet and USB, to connect the one or more userdevices 540 and 550 to local security and automation equipment. The oneor more user devices 540 and 550 may connect locally to the monitoringsystem and its sensors and other devices. The local connection mayimprove the speed of status and control communications becausecommunicating through the network 505 with a remote server (e.g., themonitoring application server 560) may be significantly slower.

Although the one or more user devices 540 and 550 are shown ascommunicating with the control unit server 510, the one or more userdevices 540 and 550 may communicate directly with the sensors and otherdevices controlled by the control unit server 510. In someimplementations, the one or more user devices 540 and 550 replace thecontrol unit server 510 and perform the functions of the control unitserver 510 for local monitoring and long range/offsite communication.

In other implementations, the one or more user devices 540 and 550receive monitoring system data captured by the control unit server 510through the network 505. The one or more user devices 540, 550 mayreceive the data from the control unit server 510 through the network505 or the monitoring application server 560 may relay data receivedfrom the control unit server 510 to the one or more user devices 540 and550 through the network 505. In this regard, the monitoring applicationserver 560 may facilitate communication between the one or more userdevices 540 and 550 and the monitoring system.

In some implementations, the one or more user devices 540 and 550 may beconfigured to switch whether the one or more user devices 540 and 550communicate with the control unit server 510 directly (e.g., throughlink 538) or through the monitoring application server 560 (e.g.,through network 505) based on a location of the one or more user devices540 and 550. For instance, when the one or more user devices 540 and 550are located close to the control unit server 510 and in range tocommunicate directly with the control unit server 510, the one or moreuser devices 540 and 550 use direct communication. When the one or moreuser devices 540 and 550 are located far from the control unit server510 and not in range to communicate directly with the control unitserver 510, the one or more user devices 540 and 550 use communicationthrough the monitoring application server 560.

Although the one or more user devices 540 and 550 are shown as beingconnected to the network 505, in some implementations, the one or moreuser devices 540 and 550 are not connected to the network 505. In theseimplementations, the one or more user devices 540 and 550 communicatedirectly with one or more of the monitoring system components and nonetwork (e.g., Internet) connection or reliance on remote servers isneeded.

In some implementations, the one or more user devices 540 and 550 areused in conjunction with only local sensors and/or local devices in ahouse. In these implementations, the system 500 only includes the one ormore user devices 540 and 550, the sensors 520, the module 522, and thecamera 530. The one or more user devices 540 and 550 receive datadirectly from the sensors 520, the module 522, and the camera 530 andsends data directly to the sensors 520, the module 522, and the camera530. The one or more user devices 540, 550 provide the appropriateinterfaces/processing to provide visual surveillance and reporting.

In other implementations, the system 500 further includes network 505and the sensors 520, the module 522, the camera 530, and the thermostat534 are configured to communicate sensor and image data to the one ormore user devices 540 and 550 over network 505 (e.g., the Internet,cellular network, etc.). In yet another implementation, the sensors 520,the module 522, the camera 530, and the thermostat 534 (or a component,such as a bridge/router) are intelligent enough to change thecommunication pathway from a direct local pathway when the one or moreuser devices 540 and 550 are in close physical proximity to the sensors520, the module 522, the camera 530, and the thermostat 534 to a pathwayover network 505 when the one or more user devices 540 and 550 arefarther from the sensors 520, the module 522, the camera 530, and thethermostat 534,. In some examples, the system leverages GPS informationfrom the one or more user devices 540 and 550 to determine whether theone or more user devices 540 and 550 are close enough to the sensors520, the module 522, the camera 530, and the thermostat 534 to use thedirect local pathway or whether the one or more user devices 540 and 550are far enough from the sensors 520, the module 522, the camera 530, andthe thermostat 534 that the pathway over network 505 is required. Inother examples, the system leverages status communications (e.g.,pinging) between the one or more user devices 540 and 550 and thesensors 520, the module 522, the camera 530, and the thermostat 534 todetermine whether communication using the direct local pathway ispossible. If communication using the direct local pathway is possible,the one or more user devices 540 and 550 communicate with the sensors520, the module 522, the camera 530, and the thermostat 534 using thedirect local pathway. If communication using the direct local pathway isnot possible, the one or more user devices 540 and 550 communicate withthe sensors 520, the module 522, the camera 530, and the thermostat 534using the pathway over network 505.

In some implementations, the system 500 provides end users with accessto images captured by the camera 530 to aid in decision making. Thesystem 500 may transmit the images captured by the camera 530 over awireless WAN network to the user devices 540 and 550. Becausetransmission over a wireless WAN network may be relatively expensive,the system 500 uses several techniques to reduce costs while providingaccess to significant levels of useful visual information.

In some implementations, a state of the monitoring system and otherevents sensed by the monitoring system may be used to enable/disablevideo/image recording devices (e.g., the camera 530). In theseimplementations, the camera 530 may be set to capture images on aperiodic basis when the alarm system is armed in an “Away” state, butset not to capture images when the alarm system is armed in a “Stay”state or disarmed. In addition, the camera 530 may be triggered to begincapturing images when the alarm system detects an event, such as analarm event, a door opening event for a door that leads to an areawithin a field of view of the camera 530, or motion in the area withinthe field of view of the camera 530. In other implementations, thecamera 530 may capture images continuously, but the captured images maybe stored or transmitted over a network when needed.

The described systems, methods, and techniques may be implemented indigital electronic circuitry, computer hardware, firmware, software, orin combinations of these elements. Apparatus implementing thesetechniques may include appropriate input and output devices, a computerprocessor, and a computer program product tangibly embodied in amachine-readable storage device for execution by a programmableprocessor. A process implementing these techniques may be performed by aprogrammable processor executing a program of instructions to performdesired functions by operating on input data and generating appropriateoutput. The techniques may be implemented in one or more computerprograms that are executable on a programmable system including at leastone programmable processor coupled to receive data and instructionsfrom, and to transmit data and instructions to, a data storage system,at least one input device, and at least one output device. Each computerprogram may be implemented in a high-level procedural or object-orientedprogramming language, or in assembly or machine language if desired; andin any case, the language may be a compiled or interpreted language.Suitable processors include, by way of example, both general and specialpurpose microprocessors. Generally, a processor will receiveinstructions and data from a read-only memory and/or a random accessmemory. Storage devices suitable for tangibly embodying computer programinstructions and data include all forms of non-volatile memory,including by way of example semiconductor memory devices, such asErasable Programmable Read-Only Memory (EPROM), Electrically ErasableProgrammable Read-Only Memory (EEPROM), and flash memory devices;magnetic disks such as internal hard disks and removable disks;magneto-optical disks; and Compact Disc Read-Only Memory (CD-ROM). Anyof the foregoing may be supplemented by, or incorporated in,specially-designed ASICs (application-specific integrated circuits).

It will be understood that various modifications may be made. Forexample, other useful implementations could be achieved if steps of thedisclosed techniques were performed in a different order and/or ifcomponents in the disclosed systems were combined in a different mannerand/or replaced or supplemented by other components. Accordingly, otherimplementations are within the scope of the disclosure.

What is claimed is:
 1. A method comprising: receiving, by a system andfrom a sensor at a property, sensor data indicating an event in aheating, ventilation, and air conditioning (“HVAC”) system that providesconditioned air to the property and generates HVAC system data thatreflects an attribute of the HVAC system; receiving, by the system andfrom the HVAC system, HVAC data; receiving, by the system, dataindicating that the property is unoccupied; determining, by the systemand using the sensor data and the HVAC data, that at least one of one ormore components in the HVAC system likely failed; in response todetermining that the at least one of the one or more components in theHVAC system likely failed and receiving the data indicating that theproperty is unoccupied, causing, by the system and using the sensor dataand the HVAC data, performance of an action, wherein causing performanceof the action comprises: initiating, while the property is unoccupied, atest of the HVAC system; and training, using second sensor data capturedduring the test, a model to indicate the likely failure of the at leastone of the one or more components.
 2. The method of claim 1, comprising:determining, by providing the HVAC data as input to the model, whetherthe at least one of the one or more components in the HVAC system likelyfailed; and in response to determining that the at least one of the oneor more components in the HVAC system has not likely failed using theHVAC data as input to the model, determining, using the sensor data,whether the at least one of the one or more components in the HVACsystem likely failed, wherein training the model is responsive todetermining that the at least one of the one or more components in theHVAC system likely failed using the sensor data.
 3. The method of claim1, wherein determining that the at least one of the one or morecomponents in the HVAC system likely failed comprises determining, byproviding the sensor data and the HVAC data as input to a model, whetherthe at least one of the one or more components in the HVAC system likelyfailed.
 4. The method of claim 3, comprising receiving, as output fromthe model, data that identifies the at least one component from the oneor more components and a likelihood that the at least one componentfailed.
 5. The method of claim 1, wherein causing the performance of theaction comprises: causing, using the sensor data from the test and theHVAC data and data from a historical database that indicates failuresand corresponding corrective actions, performance of the action.
 6. Themethod of claim 1, wherein causing the performance of the actioncomprises performing, by the system, the action to correct the likelyfailure.
 7. The method of claim 1, wherein causing performance of theaction comprises: requesting, from a user device, status information forthe HVAC system; receiving, from the user device, the status informationfor the HVAC system; and training, using the status information and theHVAC data, a model.
 8. A system comprising one or more computers and oneor more storage devices on which are stored instructions that areoperable, when executed by the one or more computers, to cause the oneor more computers to perform operations comprising: receiving, from asensor at a property, sensor data indicating an event in a heating,ventilation, and air conditioning (“HVAC”) system that providesconditioned air to the property and generates HVAC system data thatreflects an attribute of the HVAC system; receiving, from the HVACsystem, HVAC data; receiving data indicating that the property isunoccupied; determining, using the sensor data and the HVAC data, thatat least one of one or more components in the HVAC system has likelybeen serviced; in response to determining that the at least one of theone or more components in the HVAC system has likely failed, beenserviced and receiving the data indicating that the property isunoccupied, causing, using the sensor data and the HVAC data,performance of an action, wherein causing performance of the actioncomprises: initiating, while the property is unoccupied, a test of theHVAC system; and training, using the sensor data and data capturedduring the test, a model to indicate the likely service that wasperformed on the at least one of the one or more components.
 9. Thesystem of claim 8, the operations comprising: determining, by providingthe HVAC data as input to the model, whether the at least one of the oneor more components in the HVAC system has likely been serviced failed;and in response to determining that the at least one of the one or morecomponents in the HVAC system has not likely been serviced using theHVAC data as input to the model, determining, using the sensor data,whether the at least one of the one or more components in the HVACsystem has likely been serviced, wherein training the model isresponsive to determining that the at least one of the one or morecomponents in the HVAC system has likely been serviced using the sensordata.
 10. The system of claim 8, wherein determining that the at leastone of the one or more components in the HVAC system has likely beenserviced comprises determining, by providing the sensor data and theHVAC data as input to a model, whether the at least one of the one ormore components in the HVAC system has likely been serviced.
 11. Thesystem of claim 10, the operations comprising receiving, as output fromthe model, data that identifies the at least one component from the oneor more components and a likelihood that the at least one component haslikely been serviced.
 12. The system of claim 8, wherein causing theperformance of the action comprises causing, using the sensor data andthe HVAC data and data from a historical database that indicates atleast one of failures or service data and corresponding correctiveactions, performance of the action.
 13. The system of claim 8, whereincausing the performance of the action comprises performing, by thesystem, the action to correct a likely failure that should have beencorrected by the service.
 14. The system of claim 8, wherein causingperformance of the action comprises: requesting, from a user device,status information for the HVAC system; receiving, from the user device,the status information for the HVAC system; and training, using thestatus information and the HVAC data, a model.
 15. One or morenon-transitory computer storage media medium encoded with instructionsthat, when executed by one or more computers, cause the one or morecomputers to perform operations comprising: receiving, by a system andfrom a sensor at a property, sensor data indicating an event in aheating, ventilation, and air conditioning (“HVAC”) system configured toprovide conditioned air to the property and generates HVAC system datathat reflects an attribute of the HVAC system; receiving, by the systemand from the HVAC system, HVAC data; determining, by the system andusing the sensor data and the HVAC data as input to a model, that atleast one of one or more components in the HVAC system are likelyoperating in a first state; in response to determining that the at leastone of the one or more components in the HVAC system were likelyoperating in the first state: analyzing, by the system, second sensordata captured by a second sensor at the property; determining, using thesecond sensor data, that the one or more components in the HVAC systemlikely were not operating in the first state; and in response todetermining that the one or more components in the HVAC system likelywere not operating in the first state and using the second sensor data,updating the model.
 16. The computer storage media of claim 15, theoperations comprising: in response determining that the one or morecomponents in the HVAC system likely were not operating in the firststate, causing performance of an action comprising training, using thesensor data, a model to indicate the likely failure of the at least oneof the one or more components.
 17. The computer storage media of claim16, the operations comprising: determining, by providing the HVAC dataas input to the model, whether the at least one of the one or morecomponents in the HVAC system likely failed; and in response todetermining that the at least one of the one or more components in theHVAC system has not likely failed using the HVAC data as input to themodel, determining, using the sensor data, whether the at least one ofthe one or more components in the HVAC system likely failed, whereintraining the model is responsive to determining that the at least one ofthe one or more components in the HVAC system likely failed using thesensor data.
 18. The computer storage media of claim 15, whereindetermining that the at least one of the one or more components in theHVAC system likely failed comprises determining, by providing the sensordata and the HVAC data as input to a model, whether the at least one ofthe one or more components in the HVAC system likely failed.
 19. Thecomputer storage media of claim 15, wherein the first state is a healthystate.
 20. The computer storage media of claim 15, wherein the secondsensor data is captured by the sensor at the property that is the samesensor as the second sensor.